How does Playment work?

With nothing more than data and guidelines, Playment can go out and grab trained crowd labor for any particular type of tasks. HI experts build custom instructions and manage end-to-end training models for crowd qualification. The shared data then passes through a customized workflow:

Artificial Intelligence step –> To measure the confidence level

If the confidence level is lesser than the threshold, it’s sent to the trained labor pool. There is a predictive model continuously monitoring accuracy optimization and re-runs the task(s) until the quality bar is met.

Here’s the example of Playment’s QA system for autonomous driving annotations,

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How does Traditional Crowdsourcing work?

With traditional crowdsourcing like Mechanical Turk, you manually define instructions and quality metrics. Obviously, this breaks down when you are talking about multiple classes with hundreds or thousands of images, text or any kind of data. With the Playment approach, nothing is done by you, we do end-to-end project management from setting up the process (workflow) till sharing labeled data. We use our proprietary QA mechanism and complex machine learning models available. Therefore, you can have confidence that your data is proven to be accurate.